Does EASL support Retrieval-Augmented Generation (RAG)?

Yes. EASL supports RAG workflows by preparing the clean, current, and structured data that RAG models depend on. The platform can ingest unstructured documents, extract the meaningful elements, normalize them, and deliver consistent outputs to vector databases, embedding pipelines, or model-training environments.

For organizations exploring AI, EASL removes the heavy lifting associated with data prep and lets teams focus on experimentation and model refinement rather than cleanup and rework.